When caching is done correctly, you never go down, save significant infrastructure costs, and have globally unbeatable performance. However, caching is known as one of the two hardest problems in computer science for a reason. It turns out that GraphQL and Federation make caching a breeze. Max, the CEO at Stellate, shares what they have learned from caching hundreds of federated GraphQL APIs at scale that you can apply to your API to make them indestructible.

We currently worked with an API that had to scale to serve multiple regions and millions of users. Introducing caching for such numbers is a common and battle-tested way to reduce costs. With services like Stellate, this is no longer impossible even when using GraphQL.

That is great news, however, also poses some challenges. We need to pay attention to how structure our types so we can fully utilize caching.

How to rethink some GraphQL schema designs so we can have the best of the data-driven paradigm of GQL and have amazing caching capabilities at the same time?

Join Alexis, Principal Engineer at Moonpig, as he explains how they built a scalable Federated GraphQL backend using AWS serverless (Lambda, SNS, SQS, DynamoDB) and a federated architecture. Discover how their event-driven approach and custom caching strategies keep their system fast and adaptable for diverse client needs, along with a sneak peek at future performance improvements.

In this talk, we're unpacking GraphQL Fusion, a new approach that makes building distributed GraphQL APIs easier. We'll explore how this approach lets your teams work independently by owning different parts of the company's graph and cover how you can reshape subgraphs to follow your company's rules. Come learn about this powerful tool that brings efficiency and customization to your GraphQL operations.